• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of Korean Society of Forest Science
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• v.33 no.1
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• pp.33-58
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• 1977

A bark comprises about 10 to 20 percents of a typical log by volume, and is generally considered as an unwanted residue rather than a potentially valuable resourses. As the world has been confronted with decreasing forest resources, natural resources pressure dictate that a bark should be a raw material instead of a waste. The utilization of the largely wasted bark of genus Pinus, Quercus, and Populus grown in Korea can be enhanced by learning its physical and mechanical properties. However, the study of tree bark grown in Korea have never been undertaken. In the present paper, an investigative study is carried out on the bark of three genus, eleven species representing not only the major bark trees but major species currently grown in Korea. For each species 20 trees were selected, at Suweon and Kwang-neung areas, on the same basis of the diameter class at the proper harvesting age. One $200cm^2$ segment of bark was obtained from each tree at brest height. Physical properties of bark studied are: bark density, moisture content of green bark (inner-, outer-, and total-bark), fiber saturation point, hysteresis loop, shrinkage, water absorption, specific heat, heat of wetting, thermal conductivity, thermal diffusivity, heat of combustion, and differential thermal analysis. The mechanical properties are studied on bending and compression strength (radial, longitudinal, and tangential). The results may be summarized as follows: 1. The oven-dry specific gravities differ between wood and bark, further more even for a given bark sample, the difference is obersved between inner and outer bark. 2. The oven-dry specific gravity of bark is higher than that of wood. This fact is attributed to the anatomical structure whose characters are manifested by higher content of sieve fiber and sclereids. 3. Except Pinus koraiensis, the oven-dry specific gravity of inner bark is higher than that of outer bark, which results from higher shrinkage of inner bark. 4. The moisture content of bark increases with direct proportion to the composition ratio of sieve components and decreases with higher percent of sclerenchyma and periderm tissues. 5. The possibility of determining fiber saturation point is suggested by the measuring the heat of wetting. With the proposed method, the fiber saturation point of Pinus densiflora lies between 26 and 28%, that of Quercus accutissima ranges from 24 to 28%. These results need be further examined by other methods. 6. Contrary to the behavior of wood, the bark shrinkage is the highest in radial direction and the lowest in longitudinal direction. Quercus serrata and Q. variabilis do not fall in this category. 7. Bark shows the same specific heat as wood, but the heat of wetting of bark is higher than that of wood. In heat conductivity, bark is lower than wood. From the measures of oven-dry specific gravity (${\rho}d$) and moisture fraction specific gravity (${\rho}m$) is devised the following regression equation upon which heat conductivity can be calculated. The calculated heat conductivity of bark is between $0.8{\times}10^{-4}$ and $1.6{\times}10^{-4}cal/cm-sec-deg$. $$K=4.631+11.408{\rho}d+7.628{\rho}m$$ 8. The bark heat diffusivity varies from $8.03{\times}10^{-4}$ to $4.46{\times}10^{-4}cm^2/sec$. From differential thermal analysis, wood shows a higher thermogram than bark under ignition point, but the tendency is reversed above ignition point. 9. The modulus of rupture for static bending strength of bark is proportional to the density of bark which in turn gives the following regression equation. M=243.78X-12.02 The compressive strength of bark is the highest in radial direction, contrary to the behavior of wood, and the compressive strength of longitudinal direction follows the tangential one in decreasing order.